Model-based testing is a software testing technique in which test cases are derived from a model that describes the functional aspects of system under test. The testing requirements are understood by the testers and converted to business models. The business models are then used for automatically generating the test cases. Model-based testing is efficient and in case of any changes facilitates in automatically identifying impacted test cases. Many enterprises nowadays are willing to adopt model-based testing as it eliminates the need for manual test design. Further, some of their products are in maintenance phase and therefore already have numerous existing test cases. The enterprises need to categorize the existing test cases based on their functionalities for model-based testing.
Conventionally, various systems and methods exist for categorizing test cases for model based testing. For example, the enterprises manually categorize the test cases and group them based on similar functionalities. However, manually categorizing the test cases requires a lot of time and effort. Further, manually categorizing the test cases is costly, prone to errors and inefficient. Enterprises are hesitant to move to model-based testing technique due to the aforesaid reasons.
In light of the abovementioned disadvantages, there is a need for a system and method for automatically categorizing test cases for model based testing. Further, there is a need for a system and method that analyzes the existing test cases and create groups of similar test cases. Furthermore, there is a need for a system and method that is capable of analyzing and subgrouping the created groups. In addition, there is a need for a system and method that facilitates in naming the created groups and subgroups. Also, there is a need for an efficient and inexpensive system and method that facilitates in optimally categorizing the test cases with minimal human intervention.